Dashboard of sentiment in Austrian social media during COVID-19
Max Pellert, Jana Lasser, Hannah Metzler, David Garcia

TL;DR
This paper presents a real-time sentiment monitoring dashboard for Austrian social media during COVID-19, revealing emotional trends and patterns linked to pandemic events and media reporting.
Contribution
It introduces a multi-source, automated sentiment analysis tool with a publicly accessible dashboard, providing insights into collective emotions during COVID-19 in Austria.
Findings
Spikes in anxiety linked to specific events.
Decrease in anger over time.
Long-lasting emotional changes up to 12 weeks.
Abstract
To track online emotional expressions of the Austrian population close to real-time during the COVID-19 pandemic, we build a self-updating monitor of emotion dynamics using digital traces from three different data sources. This enables decision makers and the interested public to assess issues such as the attitude towards counter-measures taken during the pandemic and the possible emergence of a (mental) health crisis early on. We use web scraping and API access to retrieve data from the news platform derstandard.at, Twitter and a chat platform for students. We document the technical details of our workflow in order to provide materials for other researchers interested in building a similar tool for different contexts. Automated text analysis allows us to highlight changes of language use during COVID-19 in comparison to a neutral baseline. We use special word clouds to visualize that…
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